In this contributed article, technology writer and blogger Kayla Matthews suggests that when companies depend on predictive analytics platforms for inventory management, they can avoid pitfalls and succeed in demanding marketplaces. The lack of effective inventory management practices can lead to upset customers, plunging profits and productivity losses. Fortunately, technology offers assistance in ways that weren’t possible in earlier eras.

Physicians are increasingly using AI technologies to treat patients with superhuman speed and performance, and predictive analytics will be key to delivering more effective, proactive, and quality care. Stephen Wheat, Director of HPC Pursuits at Hewlett Packard Enterprise, explores how we can identify health risks using pattern recognition and AI.

In this contributed article, freelance human Avery Phillips discusses how big data technology coupled with predictive analytics combine to constitute a new area of law enforcement – predictive policing. While the tension around predictive policing’s ethical validity remains, results seem to be positive enough in preventing crime for it to become a more commonly used method of policing.

The following is a discussion with Vipin Kumar, Regents Professor and William Norris Chair in Large Scale Computing at University of Minnesota; ACM Fellow 2015. The Association of Computing Machinery (ACM) just concluded a celebration of 50 years of the ACM A.M. Turing Award (commonly known as the “Nobel Prize of computing”) with a two-day conference in San Francisco. The conference brought together some of the brightest minds in computing to explore how computing has evolved and where the field is headed.

Reach Analytics, a leading predictive platform for marketing teams, announced the launch of new-to-market automated response modeling capabilities. The new features are now live and available for use by marketers to increase campaign response rates.

In this contributed article, Jason Miller, Industrial Applications Engineer at Alpine Data discusses the new PFA standard that takes a good step forward from the previous PMML standard. A shift to PFA has the potential to be a watershed event in predictive analytics.

Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Learn more by downloading this Guide to Predictive Analytics.

I recently caught up with Ankur Goyal, Vice President of Engineering at MemSQL, to get an inside look at the new era of predictive analytics. Ankur runs engineering at MemSQL. He was one of the first employees at MemSQL starting in 2011, and has actively driven growth of the team since then.

The pace at which the world creates data will never be this slow again. And much of this new data we’re creating is unstructured, textual data. Emails. Word documents. News articles. Blogs. Reviews. Research reports… Understanding what’s in this text – and what isn’t, and what matters – is critical to an organization’s ability to understand the environments in which it operates. Its competitors. Its customers. Its weaknesses and its opportunities.

Using predictive analytics involves understanding and preparing the data, defining the predictive model, and following the predictive process. Predictive models can assume many shapes and sizes, depending on their complexity and the application for which they are designed. The first step is to understand what questions you are trying to answer for your organization.

Industry Perspectives

In this special guest feature, Amnon Drori, Co-founder and CEO of Octopai, discusses how for many organizations, GDPR may be the biggest data challenge they have ever faced – but it also provides organizations with an opportunity to truly own their data. By implementing a smart system that will ensure that they are able to find the data in their systems at will, organizations will ensure that they are GDPR-compliant – and have the opportunity to utilize all their data to help their organizations run more efficiently and profitably. [Read More...]

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As a company that specializes in training AI systems, we know only too well that AI systems do precisely what they are taught to do. Models are only as good as their mathematical construction and the data they are trained on. Algorithms that are biased will end up doing things that reflect that bias.